A large data base of normal and abnormal electrocardiograms will be developed with cooperation of senven hospitals. Czrdiac abnormalities will be documented by cardiac catheterization and other investigative techniques. All record samples will be stratified according to constitutional variables such as age, race, sex, and others. For later diagnostic classification of the ECG records, multivariate analysis procedures are being considered. A limited number of normal children will be followed in longitudinal fashion by taking ECG records at regular time intervals starting with the first day of life. The information content of the electrocardiogram in terms of prognosis and prediction will be studied in adults for the following disease categories: 1. Coronary artery disease; 2. Hypertensive cardiovascular disease; 3. Chronic obstructive pulmonary disease. Records are being obtained at regular time intervals until an event such as myocardial infarct or cardiac death occurs. Tracings from patients with events will be compared longitudinally with those who had an uneventful course of disease. In order to improve sensitivity and specificity of ECG exercise tests, multivariate analysis techniques will be applied to large record samples from normals and patients with documented coronary artery disease. It is hoped to achieve similar improvements as were achieved in the classification of resting electrocardiograms.